Department of Chemical Engineering, National Institute of Technology, Trichirappalli 620015, India.
Department of Chemical Engineering, National Institute of Technology, Trichirappalli 620015, India.
Ecotoxicol Environ Saf. 2015 Nov;121:236-43. doi: 10.1016/j.ecoenv.2015.03.027. Epub 2015 Apr 11.
Energy efficient designs are receiving increasing attention in various fields of engineering. Heating ventilation and air conditioning (HVAC) control system designs involve improved energy usage with an acceptable relaxation in thermal comfort. In this paper, real time data from a building HVAC system provided by BuildingLAB is considered. A resistor-capacitor (RC) framework for representing thermal dynamics of the building is estimated using particle swarm optimization (PSO) algorithm. With objective costs as thermal comfort (deviation of room temperature from required temperature) and energy measure (Ecm) explicit MPC design for this building model is executed based on its state space representation of the supply water temperature (input)/room temperature (output) dynamics. The controllers are subjected to servo tracking and external disturbance (ambient temperature) is provided from the real time data during closed loop control. The control strategies are ported on a PIC32mx series microcontroller platform. The building model is implemented in MATLAB and hardware in loop (HIL) testing of the strategies is executed over a USB port. Results indicate that compared to traditional proportional integral (PI) controllers, the explicit MPC's improve both energy efficiency and thermal comfort significantly.
节能设计在各个工程领域受到越来越多的关注。暖通空调（HVAC）控制系统的设计涉及到提高能源利用率，同时在热舒适度方面可以有一定程度的放松。本文考虑了由 BuildingLAB 提供的建筑物 HVAC 系统的实时数据。使用粒子群优化（PSO）算法估计了代表建筑物热动态的电阻-电容（RC）框架。针对该建筑物模型，以客观成本（室温与所需温度的偏差）和能量度量（Ecm）为目标，基于其供水温度（输入）/室温（输出）动态的状态空间表示执行了显式 MPC 设计。在闭环控制过程中，控制器受到伺服跟踪的影响，外部干扰（环境温度）由实时数据提供。控制策略已移植到 PIC32mx 系列微控制器平台上。建筑物模型在 MATLAB 中实现，并通过 USB 端口执行策略的硬件在环（HIL）测试。结果表明，与传统的比例积分（PI）控制器相比，显式 MPC 显著提高了能源效率和热舒适度。
